- ISBN: 9781420011180 | 1420011189
- Cover: Nonspecific Binding
- Copyright: 3/11/2008
| Preface | |
| Description of Motivating Examples | |
| Overview | |
| Dose-Finding Trial of an Experimental Treatment for Schizophrenia | |
| Clinical Trial of Recombinant Human Growth Hormone (rhGH) for Increasing Muscle Strength in the Elderly | |
| Clinical Trials of Exercise as an Aid to Smoking Cessation in Women: The Commit to Quit Studies | |
| Natural History of HIV Infection in Women: HIV Epidemiology Research Study (HERS) Cohort | |
| Clinical Trial of Smoking Cessation among Substance Abusers: OASIS Study | |
| Equivalence Trial of Competing Doses of AZT in HIV-Infected Children: Protocol 128 of the AIDS Clinical Trials Group | |
| Regression Models | |
| Overview | |
| Preliminaries | |
| Generalized Linear Models | |
| Conditionally Specified Models | |
| Directly Specified (Marginal) Models | |
| Semiparametric Regression | |
| Interpreting Covariate Effects | |
| Further Reading | |
| Methods of Bayesian Inference | |
| Overview | |
| Likelihood and Posterior Distribution | |
| Prior Distributions | |
| Computation of the Posterior Distribution | |
| Model Comparisons and Assessing Model Fit | |
| Nonparametric Bayes | |
| Further Reading | |
| Bayesian Analysis using Data on Completers | |
| Overview | |
| Model Selection and Inference with a Multivariate Normal Model: Analysis of the Growth Hormone Clinical Study | |
| Inference with a Normal Random Effects Model: Analysis of the Schizophrenia Clinical Trial | |
| Model Selection and Inference for Binary Longitudinal Data: Analysis of CTQ I | |
| Summary | |
| Missing Data Mechanisms and Longitudinal Data | |
| Introduction | |
| Full vs. Observed Data | |
| Full-Data Models and Missing Data Mechanisms | |
| Assumptions about Missing Data Mechanism | |
| Missing at Random Applied to Dropout Processes | |
| Observed-Data Posterior of Full-Data Parameters | |
| The Ignorability Assumption | |
| Examples of Full-Data Models under MAR | |
| Full-Data Models under MNAR | |
| Summary | |
| Further Reading | |
| Inference about Full-Data Parameters under Ignorability | |
| Overview | |
| General Issues in Model Specification | |
| Posterior Sampling Using Data Augmentation | |
| Covariance Structures for Univariate Longitudinal Processes | |
| Covariate-Dependent Covariance Structures | |
| Multivariate Processes | |
| Model Comparisons and Assessing Model Fit with Incomplete Data under Ignorability | |
| Further Reading | |
| Case Studies: Ignorable Missingness | |
| Overview | |
| Analysis of the Growth Hormone Study under MAR | |
| Analysis of the Schizophrenia Clinical Trial under MAR Using Random Effects Models | |
| Analysis of CTQ I Using Marginalized Transition Models under MAR | |
| Analysis of Weekly Smoking Outcomes in CTQ II Using Auxiliary Variable MAR | |
| Analysis of HERS CD4 Data under Ignorability Using Bayesian p-Spline Models | |
| Summary | |
| Models for handling Nonignorable Missingness | |
| Overview | |
| Extrapolation Factorization | |
| Selection Models | |
| Mixture Models | |
| Shared Parameter Models | |
| Model Comparisons and Assessing Model Fit in Nonignorable Models | |
| Further Reading | |
| Informative Priors and Sensitivity Analysis | |
| Overview | |
| Some Principles | |
| Parameterizing the Full-Data Model | |
| Pattern-Mixture Models | |
| Selection Models | |
| Elicitation of Expert Opinion, Construction of Informative Priors, and Formulation of Sensitivity Analyses | |
| A Note on Sensitivity Analysis in Fully Parametric Models | |
| Literature on Local Sensitivity | |
| Further Reading | |
| Case Studies: Model Specification and Data Analysis under Missing Not at Random | |
| Overview | |
| Analysis of Growth Hormone Study Using Pattern-Mixture Models | |
| Analysis of OASIS Study Using Selection and Pattern-Mixture Models | |
| Analysis of Pediatric AIDS Trial Using Mixture of Varying Coefficient Models | |
| Appendix: distributions | |
| Bibliography | |
| Index | |
| Table of Contents provided by Publisher. All Rights Reserved. |
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